solution by successive approximation
1Approximation — An approximation (represented by the symbol ≈) is an inexact representation of something that is still close enough to be useful. Although approximation is most often applied to numbers, it is also frequently applied to such things as… …
2Successive linear programming — SLP Successive Linear ProgrammingLinear programming is a powerful technique for optimisation but the requirement that all constraints be linear can make it difficult to write models that represent the real world closely enough to produce useful… …
3Relaxation (approximation) — In mathematical optimization and related fields, relaxation is a modeling strategy. A relaxation is an approximation of a difficult problem by a nearby problem that is easier to solve. A solution of the relaxed problem provides information about… …
4решение методом последовательных приближений — — [А.С.Гольдберг. Англо русский энергетический словарь. 2006 г.] Тематики энергетика в целом EN solution by successive approximation …
5Least squares — The method of least squares is a standard approach to the approximate solution of overdetermined systems, i.e., sets of equations in which there are more equations than unknowns. Least squares means that the overall solution minimizes the sum of… …
6Dynamic programming — For the programming paradigm, see Dynamic programming language. In mathematics and computer science, dynamic programming is a method for solving complex problems by breaking them down into simpler subproblems. It is applicable to problems… …
7Non-linear least squares — is the form of least squares analysis which is used to fit a set of m observations with a model that is non linear in n unknown parameters (m > n). It is used in some forms of non linear regression. The basis of the method is to… …
8Czesław Olech — Born May 22, 1931 (1931 05 22) (age 80) Pińczów, Poland Nationality Polish …
9Markov decision process — Markov decision processes (MDPs), named after Andrey Markov, provide a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker. MDPs are useful for… …
10Local convergence — In numerical analysis, an iterative method is called locally convergent if the successive approximations produced by the method are guaranteed to converge to a solution when the initial approximation is already close enough to the solution.… …
